{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "source": [
    "# Product Planning Problem\n",
    "\n",
    "A company manufactures two types of products: Product A and Product B. The company has limited resources available, including labor hours and raw materials. Each unit of Product A requires 2 labor hours and 3 units of raw material, while each unit of Product B requires 3 labor hours and 2 units of raw material. The company wants to determine the optimal production quantities of each product to maximize their total profit.\n",
    "\n",
    "Objective:\n",
    "    Maximize the total profit.\n",
    "   \n",
    "Constraints:\n",
    "\n",
    "1. The total labor hours available are limited to 100 hours.\n",
    "2. The total raw material available is limited to 80 units.\n",
    "3. The production quantities of both Product A and Product B must be non-negative integers.\n",
    "\n",
    "Decision Variables:\n",
    "\n",
    "1. Let x represent the number of units of Product A to produce.\n",
    "2. Let y represent the number of units of Product B to produce.\n",
    "\n",
    "\n",
    "Mathematical Formulation:\n",
    "    The problem can be formulated as an integer programming problem as follows:\n",
    "\n",
    "Maximize: Profit = 5x + 4y\n",
    "\n",
    "Subject to:\n",
    "\n",
    "* 2x + 3y ≤ 100 (Labor hours constraint)\n",
    "* 3x + 2y ≤ 80 (Raw material constraint)\n",
    "* x, y ≥ 0 and integers (Non-negativity and integer constraints)\n",
    "\n",
    "In this example, the decision variables x and y represent the quantities of Product A and Product B, respectively. The objective is to maximize the total profit, subject to the constraints on labor hours and raw material availability. The non-negativity and integer constraints ensure that the production quantities are valid.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Solver\n",
    "\n",
    "We gonna use Mealpy to solve this problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: Solving single objective optimization problem.\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 1, Current best: 145.0, Global best: 145.0, Runtime: 0.00616 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 2, Current best: 152.0, Global best: 152.0, Runtime: 0.00645 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 3, Current best: 143.0, Global best: 152.0, Runtime: 0.00700 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 4, Current best: 133.0, Global best: 152.0, Runtime: 0.00679 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 5, Current best: 152.0, Global best: 152.0, Runtime: 0.00547 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 6, Current best: 132.0, Global best: 152.0, Runtime: 0.00558 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 7, Current best: 138.0, Global best: 152.0, Runtime: 0.00554 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 8, Current best: 140.0, Global best: 152.0, Runtime: 0.00672 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 9, Current best: 152.0, Global best: 152.0, Runtime: 0.00560 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 10, Current best: 152.0, Global best: 152.0, Runtime: 0.00755 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 11, Current best: 152.0, Global best: 152.0, Runtime: 0.00594 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 12, Current best: 152.0, Global best: 152.0, Runtime: 0.00556 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 13, Current best: 129.0, Global best: 152.0, Runtime: 0.00568 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 14, Current best: 152.0, Global best: 152.0, Runtime: 0.00535 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 15, Current best: 141.0, Global best: 152.0, Runtime: 0.00513 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 16, Current best: 149.0, Global best: 152.0, Runtime: 0.00536 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 17, Current best: 124.0, Global best: 152.0, Runtime: 0.00565 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 18, Current best: 152.0, Global best: 152.0, Runtime: 0.00710 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 19, Current best: 130.0, Global best: 152.0, Runtime: 0.00618 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 20, Current best: 134.0, Global best: 152.0, Runtime: 0.00715 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 21, Current best: 152.0, Global best: 152.0, Runtime: 0.00602 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 22, Current best: 141.0, Global best: 152.0, Runtime: 0.00536 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 23, Current best: 116.0, Global best: 152.0, Runtime: 0.00583 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 24, Current best: 149.0, Global best: 152.0, Runtime: 0.00592 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 25, Current best: 140.0, Global best: 152.0, Runtime: 0.00497 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 26, Current best: 152.0, Global best: 152.0, Runtime: 0.00586 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 27, Current best: 152.0, Global best: 152.0, Runtime: 0.00565 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 28, Current best: 136.0, Global best: 152.0, Runtime: 0.00560 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 29, Current best: 128.0, Global best: 152.0, Runtime: 0.00636 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 30, Current best: 152.0, Global best: 152.0, Runtime: 0.00584 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 31, Current best: 137.0, Global best: 152.0, Runtime: 0.00582 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 32, Current best: 116.0, Global best: 152.0, Runtime: 0.00599 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 33, Current best: 152.0, Global best: 152.0, Runtime: 0.00557 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 34, Current best: 152.0, Global best: 152.0, Runtime: 0.00525 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 35, Current best: 152.0, Global best: 152.0, Runtime: 0.00657 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 36, Current best: 150.0, Global best: 152.0, Runtime: 0.00611 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 37, Current best: 134.0, Global best: 152.0, Runtime: 0.00537 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 38, Current best: 112.0, Global best: 152.0, Runtime: 0.00609 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 39, Current best: 152.0, Global best: 152.0, Runtime: 0.00614 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 40, Current best: 132.0, Global best: 152.0, Runtime: 0.00555 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 41, Current best: 140.0, Global best: 152.0, Runtime: 0.00667 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 42, Current best: 147.0, Global best: 152.0, Runtime: 0.00589 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 43, Current best: 152.0, Global best: 152.0, Runtime: 0.00563 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 44, Current best: 145.0, Global best: 152.0, Runtime: 0.00627 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 45, Current best: 146.0, Global best: 152.0, Runtime: 0.00558 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 46, Current best: 152.0, Global best: 152.0, Runtime: 0.00592 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 47, Current best: 147.0, Global best: 152.0, Runtime: 0.00593 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 48, Current best: 150.0, Global best: 152.0, Runtime: 0.00515 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 49, Current best: 120.0, Global best: 152.0, Runtime: 0.00477 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 50, Current best: 152.0, Global best: 152.0, Runtime: 0.00563 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 51, Current best: 152.0, Global best: 152.0, Runtime: 0.00569 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 52, Current best: 132.0, Global best: 152.0, Runtime: 0.00580 seconds\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 53, Current best: 152.0, Global best: 152.0, Runtime: 0.00737 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 54, Current best: 112.0, Global best: 152.0, Runtime: 0.00581 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 55, Current best: 128.0, Global best: 152.0, Runtime: 0.00549 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 56, Current best: 145.0, Global best: 152.0, Runtime: 0.00527 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 57, Current best: 150.0, Global best: 152.0, Runtime: 0.00500 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 58, Current best: 152.0, Global best: 152.0, Runtime: 0.00558 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 59, Current best: 131.0, Global best: 152.0, Runtime: 0.00603 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 60, Current best: 132.0, Global best: 152.0, Runtime: 0.00573 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 61, Current best: 143.0, Global best: 152.0, Runtime: 0.00501 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 62, Current best: 140.0, Global best: 152.0, Runtime: 0.00515 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 63, Current best: 122.0, Global best: 152.0, Runtime: 0.00540 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 64, Current best: 147.0, Global best: 152.0, Runtime: 0.00486 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 65, Current best: 132.0, Global best: 152.0, Runtime: 0.00542 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 66, Current best: 143.0, Global best: 152.0, Runtime: 0.00545 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 67, Current best: 152.0, Global best: 152.0, Runtime: 0.00580 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 68, Current best: 133.0, Global best: 152.0, Runtime: 0.00515 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 69, Current best: 152.0, Global best: 152.0, Runtime: 0.00527 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 70, Current best: 145.0, Global best: 152.0, Runtime: 0.00540 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 71, Current best: 138.0, Global best: 152.0, Runtime: 0.00533 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 72, Current best: 132.0, Global best: 152.0, Runtime: 0.00534 seconds\n",
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      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 74, Current best: 132.0, Global best: 152.0, Runtime: 0.00533 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 75, Current best: 128.0, Global best: 152.0, Runtime: 0.00578 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 76, Current best: 143.0, Global best: 152.0, Runtime: 0.00507 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 77, Current best: 146.0, Global best: 152.0, Runtime: 0.00528 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 78, Current best: 152.0, Global best: 152.0, Runtime: 0.00484 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 79, Current best: 152.0, Global best: 152.0, Runtime: 0.00610 seconds\n",
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      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 81, Current best: 152.0, Global best: 152.0, Runtime: 0.00679 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 82, Current best: 152.0, Global best: 152.0, Runtime: 0.00525 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 83, Current best: 148.0, Global best: 152.0, Runtime: 0.00599 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 84, Current best: 150.0, Global best: 152.0, Runtime: 0.00565 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 85, Current best: 134.0, Global best: 152.0, Runtime: 0.00683 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 86, Current best: 152.0, Global best: 152.0, Runtime: 0.00558 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 87, Current best: 128.0, Global best: 152.0, Runtime: 0.00561 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 88, Current best: 150.0, Global best: 152.0, Runtime: 0.00546 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 89, Current best: 142.0, Global best: 152.0, Runtime: 0.00472 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 90, Current best: 147.0, Global best: 152.0, Runtime: 0.00600 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 91, Current best: 149.0, Global best: 152.0, Runtime: 0.00707 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 92, Current best: 152.0, Global best: 152.0, Runtime: 0.00622 seconds\n",
      "2023/10/31 05:04:42 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 93, Current best: 150.0, Global best: 152.0, Runtime: 0.00691 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 94, Current best: 146.0, Global best: 152.0, Runtime: 0.00532 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 95, Current best: 141.0, Global best: 152.0, Runtime: 0.00629 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 96, Current best: 150.0, Global best: 152.0, Runtime: 0.00595 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 97, Current best: 144.0, Global best: 152.0, Runtime: 0.00509 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 98, Current best: 147.0, Global best: 152.0, Runtime: 0.00630 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 99, Current best: 148.0, Global best: 152.0, Runtime: 0.00598 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 100, Current best: 145.0, Global best: 152.0, Runtime: 0.00592 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 101, Current best: 131.0, Global best: 152.0, Runtime: 0.00497 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 102, Current best: 150.0, Global best: 152.0, Runtime: 0.00569 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 103, Current best: 140.0, Global best: 152.0, Runtime: 0.00545 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 104, Current best: 143.0, Global best: 152.0, Runtime: 0.00573 seconds\n",
      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 105, Current best: 129.0, Global best: 152.0, Runtime: 0.00705 seconds\n"
     ]
    },
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      "2023/10/31 05:04:43 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 106, Current best: 140.0, Global best: 152.0, Runtime: 0.00619 seconds\n",
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      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 936, Current best: 152.0, Global best: 152.0, Runtime: 0.00674 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 937, Current best: 152.0, Global best: 152.0, Runtime: 0.00550 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 938, Current best: 152.0, Global best: 152.0, Runtime: 0.00565 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 939, Current best: 152.0, Global best: 152.0, Runtime: 0.00624 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 940, Current best: 152.0, Global best: 152.0, Runtime: 0.00529 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 941, Current best: 152.0, Global best: 152.0, Runtime: 0.00516 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 942, Current best: 152.0, Global best: 152.0, Runtime: 0.00524 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 943, Current best: 152.0, Global best: 152.0, Runtime: 0.00548 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 944, Current best: 152.0, Global best: 152.0, Runtime: 0.00586 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 945, Current best: 152.0, Global best: 152.0, Runtime: 0.00585 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 946, Current best: 152.0, Global best: 152.0, Runtime: 0.00502 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 947, Current best: 152.0, Global best: 152.0, Runtime: 0.00633 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 948, Current best: 152.0, Global best: 152.0, Runtime: 0.00567 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 949, Current best: 152.0, Global best: 152.0, Runtime: 0.00597 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 950, Current best: 152.0, Global best: 152.0, Runtime: 0.00561 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 951, Current best: 152.0, Global best: 152.0, Runtime: 0.00684 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 952, Current best: 152.0, Global best: 152.0, Runtime: 0.00651 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 953, Current best: 152.0, Global best: 152.0, Runtime: 0.00638 seconds\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 954, Current best: 152.0, Global best: 152.0, Runtime: 0.00552 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 955, Current best: 152.0, Global best: 152.0, Runtime: 0.00563 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 956, Current best: 152.0, Global best: 152.0, Runtime: 0.00542 seconds\n",
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      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 995, Current best: 152.0, Global best: 152.0, Runtime: 0.00555 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 996, Current best: 152.0, Global best: 152.0, Runtime: 0.00758 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 997, Current best: 152.0, Global best: 152.0, Runtime: 0.00578 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 998, Current best: 152.0, Global best: 152.0, Runtime: 0.00707 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 999, Current best: 152.0, Global best: 152.0, Runtime: 0.00594 seconds\n",
      "2023/10/31 05:04:48 PM, INFO, mealpy.bio_based.SMA.OriginalSMA: >>>Problem: P, Epoch: 1000, Current best: 152.0, Global best: 152.0, Runtime: 0.00545 seconds\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id: 104315, target: Objectives: [152], Fitness: 152.0, solution: [ 9.13878489 27.30582784]\n",
      "Best fitness: 152.0, Best solution: {'var': array([ 9, 27])}\n"
     ]
    }
   ],
   "source": [
    "from mealpy import IntegerVar, Problem, SMA\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "class PPP(Problem):\n",
    "    def __init__(self, bounds=None, minmax=\"min\", name=\"PPP\", **kwargs):\n",
    "        self.name = name\n",
    "        super().__init__(bounds, minmax, **kwargs)\n",
    "    \n",
    "    def constrains(self, x):\n",
    "        g1 = 2*x[0] + 3*x[1] - 100\n",
    "        g2 = 3*x[0] + 2*x[1] - 80\n",
    "        return [g1, g2]\n",
    "\n",
    "    def obj_func(self, solution):\n",
    "        solution = self.decode_solution(solution) \n",
    "        x = solution[\"var\"]\n",
    "        g1, g2 = self.constrains(x)\n",
    "        profit = 5*x[0] + 4*x[1]\n",
    "        violation = max(g1, 0) + max(g2, 0)\n",
    "        return profit - violation**2\n",
    "\n",
    "## Now, we define an algorithm, and pass an instance of our *Squared* class as the problem argument. \n",
    "problem = PPP(bounds=IntegerVar(lb=(0, 0), ub=(80, 80), name=\"var\"), minmax=\"max\", name=\"PPP\")\n",
    "model = SMA.OriginalSMA(epoch=1000, pop_size=30)\n",
    "g_best = model.solve(problem)\n",
    "print(g_best)\n",
    "print(f\"Best fitness: {g_best.target.fitness}, Best solution: {model.problem.decode_solution(g_best.solution)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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